academic-rebuttal

Draft evidence-backed rebuttals correcting false impressions in venue reviews.

4|2|Updated Feb 19, 2026

Search Tags:#templates #guidelines #conference #reviewer #rebuttal #openreview #hotcrp

Ready to run

npx skills add https://github.com/drunkcoding/AgentSkillsArxiv --skill academic-rebuttal

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: academic-rebuttal
Source: https://github.com/drunkcoding/AgentSkillsArxiv/tree/main/skills/academic-rebuttal
Command: npx skills add https://github.com/drunkcoding/AgentSkillsArxiv --skill academic-rebuttal

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Drafts professional, evidence-based author responses that counter reviewer false impressions while preserving tone and credibility.

Core Features & Use Cases

False impression taxonomy and resolution playbooks for eight FI types
Stage-wise rebuttal workflow: triage, drafting, compression, and policy checks
Ready-to-use phrase templates and structured response patterns for major venues
Cross-venue guidance (OpenReview/HotCRP) and platform mechanics references

Quick Start

Provide a concise, evidence-backed rebuttal that directly addresses the top concern with explicit revision commitments.

Frequently Asked Questions about academic-rebuttal

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I write a conference rebuttal that corrects reviewer factual errors?▼

A conference rebuttal corrects reviewer false impressions by providing evidence-backed responses and explicit revision commitments. You identify factual errors in reviews and counter them with structured, professional arguments that preserve credibility.

How do I format an author response for OpenReview or HotCRP within word limits?▼

Formatting an author response for OpenReview or HotCRP requires applying venue-specific templates and policy-aware structures. You compress evidence-backed arguments into concise statements that satisfy platform word limits and explicit revision commitment requirements.

What is the best way to handle false impressions in reviewer feedback for ML conferences?▼

Handling false impressions in reviewer feedback for ML conferences involves classifying the error type and applying a targeted resolution playbook. You draft evidence-based responses that directly counter factual misunderstandings while adhering to venue policies.

Does this rebuttal workflow support both computer systems venues and ML conferences?▼

Yes, the rebuttal workflow supports computer systems venues like OSDI, SIGCOMM, and SOSP, alongside ML conferences such as NeurIPS, ICML, and ICLR. It provides cross-venue guidance and platform-specific templates for both OpenReview and HotCRP.

What are the steps to draft a rebuttal for a major computer systems conference?▼

Drafting a rebuttal involves a stage-wise workflow: triage reviews to identify false impressions, draft evidence-backed responses, compress text to meet word limits, and perform policy checks. This ensures structured, compliant author responses.